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<title>13.7.   小结（New） - Hello 算法</title>
<title>14.7.   小结（New） - Hello 算法</title>
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13.7. &nbsp; 小结（New）
14.7. &nbsp; 小结（New）
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</div>
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<a href="../../chapter_divide_and_conquer/">12. &nbsp; &nbsp; 分治</a>
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12. &nbsp; &nbsp; 分治
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12.1. &nbsp; 分治算法（New）
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12. &nbsp; &nbsp; 回溯
13. &nbsp; &nbsp; 回溯
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12.1. &nbsp; 回溯算法
13.1. &nbsp; 回溯算法
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12.2. &nbsp; 全排列问题
13.2. &nbsp; 全排列问题
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12.3. &nbsp; 子集和问题
13.3. &nbsp; 子集和问题
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12.4. &nbsp; N 皇后问题
13.4. &nbsp; N 皇后问题
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12.5. &nbsp; 小结
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13. &nbsp; &nbsp; 动态规划
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13.1. &nbsp; 初探动态规划（New）
14.1. &nbsp; 初探动态规划（New）
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13.2. &nbsp; DP 问题特性（New）
14.2. &nbsp; DP 问题特性（New）
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13.3. &nbsp; DP 解题思路（New）
14.3. &nbsp; DP 解题思路（New）
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13.4. &nbsp; 0-1 背包问题（New）
14.4. &nbsp; 0-1 背包问题（New）
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13.5. &nbsp; 完全背包问题（New）
14.5. &nbsp; 完全背包问题（New）
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13.6. &nbsp; 编辑距离问题（New）
14.6. &nbsp; 编辑距离问题（New）
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<a href="./" class="md-nav__link md-nav__link--active">
13.7. &nbsp; 小结（New）
14.7. &nbsp; 小结（New）
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<h1 id="137">13.7. &nbsp; 小结<a class="headerlink" href="#137" title="Permanent link">&para;</a></h1>
<h1 id="147">14.7. &nbsp; 小结<a class="headerlink" href="#147" title="Permanent link">&para;</a></h1>
<ul>
<li>动态规划通过将原问题分解为子问题来求解问题，并通过存储子问题的解来规避重复计算，实现高效的计算效率。子问题分解是一种通用的算法思路，在分治、动态规划、回溯中具有不同的性质。</li>
<li>不考虑时间的前提下，所有动态规划问题都可以用回溯（暴力搜索）进行求解，但递归树中存在大量的重叠子问题，效率极低。通过引入记忆化列表，可以存储所有计算过的子问题的解，从而保证重叠子问题只被计算一次。</li>
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